List and Dict Comprehensions

Learn list and dict Comprehensions

List & Dict Comprehensions

Comprehensions are one of the most loved Python features — they let you build lists and dictionaries in a single concise line, replacing what would otherwise be a multi-line loop.

List Comprehensions

The basic idea: instead of building a list with a loop and append, you describe the list directly.

Without comprehension:

With comprehension:

The general syntax is:

Filtering with a Condition

You can add an if clause to keep only elements that satisfy a condition:

Transforming Strings

Comprehensions work on any iterable, including strings and lists of strings:

Reading Input into a List

This is probably the most used comprehension in competitive programming:

Nested Comprehensions — 2D Structures

You can nest comprehensions to build 2D lists. The outer loop comes first:

Output:

Flattening a 2D List

The order here is: outer loop first (for row in matrix), inner loop second (for x in row) — same as the equivalent nested for loops written top to bottom.

if-else Inside a Comprehension

You can also use a ternary expression to transform each element conditionally. Note the position — if/else for transformation goes before the for, while if for filtering goes after:

Dict Comprehensions

Dict comprehensions build dictionaries the same way:

Filtering in Dict Comprehensions

Inverting a Dictionary

Swap keys and values — useful when you need reverse lookups:

Building a Frequency Dict

Note: this is O(n^2) because a.count(x) scans the whole list for each unique element. For large inputs use Counter instead.

Coordinate Compression in One Line

Set Comprehensions

While we're here — set comprehensions work the same way, just with curly braces and no key-value pair:

When Not to Use Comprehensions

Comprehensions shine for simple, readable transformations. Avoid them when:

• The logic requires multiple statements